CN103136671A - Product quality tracing method and product quality tracing device - Google Patents
Product quality tracing method and product quality tracing device Download PDFInfo
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- CN103136671A CN103136671A CN2011103905793A CN201110390579A CN103136671A CN 103136671 A CN103136671 A CN 103136671A CN 2011103905793 A CN2011103905793 A CN 2011103905793A CN 201110390579 A CN201110390579 A CN 201110390579A CN 103136671 A CN103136671 A CN 103136671A
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Abstract
The invention discloses a product quality tracing method and a product quality tracing device. The product tracing method comprises the steps of producing judgment rules, corresponding to product batches, of raw material combination and unqualified product raw material sources, wherein the judgment rules are based on product production plans; producing products according to the product raw material combination; and in response to the fact that quality problems occur in the products, determining the unqualified product raw material sources according to the judgment rules.
Description
Technical field
The present invention relates to Product quality and safety, particularly product quality retroactive method and device.
Background technology
In recent years, the Product quality and safety accident occurs time and again, and for example, baby milk qi enterobacteria exceeds standard, and melamine poison milk powder case and automotive global are recalled event.Reply burst Product quality and safety event need to be set up the Product quality and safety fast reaction mechanism, and the location does not meet the raw material sources of product quality fast, thereby Accident prevention and loss further enlarge.
The measure of existing reply burst quality safety event is located by the product that detects problem after accident occurs usually, for example, 1) the direct-detection products material, often due to raw-food material approach exhaustion or difficult the preservation, and be difficult for obtaining.2) set up product quality and review network.Review network by the information of record product in production, processing, storage, transportation and sale links, the information flow network of foundation from the product starting material to finished product.By the reasoning on the product back-tracing network, can judge the underproof possibility of raw material, yet the result of reasoning can't directly be determined defective raw material.Take poisonous milk powder as example, because the milk raw material of a plurality of milking stations mixes in Milk Products Plant, therefore be difficult to review the milk raw material source that causes quality accidents.
The key of setting up the product quality fast reaction mechanism is to find the root of product safety accident, therefore needs a kind of quick and precisely location to cause the method that the products material of Product quality and safety accident is originated.
Summary of the invention
Based on the problems referred to above, the invention provides a kind of product quality retroactive method and device.
According to a first aspect of the invention, provide a kind of product quality retroactive method, comprising: the product-based production schedule produces the decision rule of originating corresponding to products material combination and the underproof products material of product batches; According to described products material combinations produce product; Quality problems occur in response to product, determine underproof products material source according to decision rule.
According to a second aspect of the invention, provide a kind of product quality retrospective device, comprising: optimize module, be configured to the product-based production schedule and produce the decision rule of originating corresponding to products material combination and the underproof products material of product batches; The production module is configured to according to described products material combinations produce product; Determination module is configured to quality problems occur in response to product, determines underproof products material source according to decision rule.
According to product quality retroactive method and the device of the embodiment of the present invention, can quick and precisely locate the raw material sources that cause quality accidents, thereby Accident prevention and loss enlarge further.
Description of drawings
By reference to the accompanying drawings, by describing method and apparatus in detail with reference to following embodiment, will be better understood the present invention itself, preferred embodiment and objects and advantages of the present invention, wherein:
Fig. 1 illustrates a kind of product quality retroactive method according to the embodiment of the present invention;
Fig. 2 illustrates product quality retroactive method flow process according to an embodiment of the invention;
Fig. 3 illustrates product quality retroactive method flow process according to an embodiment of the invention;
Fig. 4 illustrates a kind of product quality retrospective device according to the embodiment of the present invention; And
Fig. 5 has schematically shown and can realize the block diagram of computing equipment according to an embodiment of the invention.
Embodiment
Below in conjunction with a kind of product quality retroactive method and the device of accompanying drawing description according to the embodiment of the present invention, will be better understood objects and advantages of the present invention.
Fig. 1 illustrates a kind of product quality retroactive method according to the embodiment of the present invention, and at step S101, the product-based production schedule produces the decision rule of originating corresponding to products material combination and the underproof products material of product batches; At step S102, according to described products material combinations produce product corresponding to product batches; At step S103, quality problems appear in response to product, determine underproof products material source according to decision rule.
Fig. 2 illustrates product quality retroactive method flow process according to an embodiment of the invention, comprise step S201, obtain the number of raw material sources, product batches and the problematic raw material sources of possibility, wherein the production plan comprises products material source, product batches, product quantity, quality, raw material proportioning, therefore raw material sources, product batches can be obtained in the works from production, and the number of the problematic raw material sources of possibility can obtain according to the historical feedback record of product quality.
At step S202, number based on the raw material sources that obtain, product batches and the problematic raw material sources of possibility is encoded and produces encoder matrix possible assay at two-dimensional space, the row vector of wherein said encoder matrix is corresponding to underproof products material source, and the column vector of described encoder matrix is corresponding to product batches, the coding distance between any two capable vectors of encoder matrix according to may problematic products material the number in source determine.
At two-dimensional space, possible assay is encoded, produces encoder matrix A:
The row vector representation is A
i=[a
i1...., a
iM], the row vector is corresponding to the combination in products material source
Column vector is expressed as A
J=[a
1j...., a
Nj]
T, column vector is corresponding to product batches m
i,
Wherein the row vector satisfies | A
i·-A
J| 〉=C,
Wherein column vector satisfies ∑
iA
ijWeight (n
i)=weight (m
j), 1≤i≤N, the quality of weight () expression starting material or product.
Wherein the coding of two-dimensional space need to meet following two conditions:
1) | s (f
-1(n
k))-s (f
-1(n
j)) | 〉=C, C 〉=0,1≤k, j≤N and k ≠ j, N ∈ positive integer;
2) q (m
i)=q (f (m
i)), 1≤i≤M, M ∈ positive integer;
M wherein
iRepresent i product batches; n
jAnd n
kRepresent respectively j and k raw material sources; The component function of f () expression product batches; f
-1The inverse function of the component function of () expression product batches; Q () expression calculated mass function; S () expression binary coding function; The express possibility number in underproof products material source of C.
At step S203, according to determine the products material combination of this product batches corresponding to the underproof bit of expression assay in the column vector of product batches; Particularly, according to the products material combination of determining this product batches corresponding to the underproof bit of expression assay corresponding with single problematic raw material sources in the column vector of product batches.At step S204, according to the vectorial decision rule of determining the substandard product source of row corresponding to underproof products material source.At step S205, according to described products material combinations produce product corresponding to product batches.At step S206, quality problems appear in response to product, obtain the assay of the product batches relevant to decision rule, originate according to assay and the unique definite underproof products material of decision rule.
Fig. 3 illustrates product quality retroactive method flow process according to an embodiment of the invention, at step S301, obtains the number of raw material sources, product batches and the problematic raw material sources of possibility.At step S302, obtain the security risk coefficient of raw material sources, the security risk coefficient of raw material sources can be added up and obtain the historical feedback record of product quality.At step S303, at two-dimensional space, possible assay is encoded and produced encoder matrix, wherein the row vector of encoder matrix is corresponding to underproof products material source, and the column vector of encoder matrix is corresponding to product batches, and the coding distance between any two capable vectors of encoder matrix is determined according to number that may problematic raw material sources.At step S304, according to determine the products material combination of this product batches corresponding to the underproof bit of expression assay in the column vector of product batches, particularly, according to the products material combination of determining this product batches corresponding to the underproof bit of expression assay corresponding with single problematic raw material sources in the column vector of product batches.At step S305, calculate the security risk of described products material combination, choose the products material combination of security risk minimum.At step S306, according to the vectorial decision rule of determining the substandard product source of row corresponding to underproof products material source.At step S307, produce product according to the material combination corresponding to the security risk minimum of product batches.At step S308, quality problems appear in response to product, obtain the assay of the product batches relevant to decision rule, originate according to assay and the unique definite underproof products material of decision rule.
According to one embodiment of present invention, wherein choosing the raw-food material combination that can locate defective food sources also comprises: the security risk of obtaining the raw-food material source; Calculating meets the security risk of the raw-food material combination of food production plan; Choose the raw-food material combination of security risk minimum.
[the first embodiment]
to produce breast product processed as example, according to the production plan, with from milking station A, B, the milk of C and four milking stations of D is that raw material sources produce dairy products, comprise M, N, P, four batches of Q, wherein the dairy products of each batch need the milk of 3 volumes, and determine that according to historical record the milking station that quality problems may occur only has one, method according to the embodiment of the present invention, at two-dimensional space, possible assay is encoded, determine coding spacing between any two capable vectors according to number that may problematic raw material sources, the row vector of wherein said two-dimensional space is corresponding to underproof milking station A, B, the combination of C and D, and the column vector of described two-dimensional space is corresponding to product batches M, N, P, Q, in the situation that only have a food sources quality problems to occur, " 1 " represents that the product of certain batch goes wrong, " 0 " represents that the product of certain batch is qualified, the following encoder matrix A that meets the embodiment of the present invention that illustrates.
according to the products material combination of determining this product batches corresponding to the underproof bit of expression assay corresponding with single problematic raw material sources in the column vector of product batches, the combination of batch M is the milk from milking station C and D, the combination of batch N is the milk from milking station D, the combination of batch P is the milk from milking station A and B, the combination of batch Q is the milk from milking station B, again according to the quality of all batches and the principle of mass conservation of rule of origin, calculate the portfolio ratio of the products material of each batch, table 1 illustrates the portfolio ratio of the products material of each batch, wherein the proportioning of batch M is the milk of two volume C milking stations and the milk of 1 volume D milking station, the proportioning of batch N is the milk of three volume D milking stations, the proportioning of batch P is the milk of two each and every one volume A milking stations and the milk of a volume B milking station, the proportioning of batch Q is the milk of three volume B milking stations.
Table 1
| Food batch | The raw-food material proportioning |
| M | C 2D 1 |
| N | D 3 |
| P | A 2B 1 |
| Q | B 3 |
Determine the decision rule in substandard product source according to the row vector of originating corresponding to underproof products material in encoder matrix A, decision rule when table 2 illustrates product and quality problems occur, obtain the assay of the product batches relevant to decision rule, originate according to assay and the unique definite underproof products material of decision rule, wherein " 1 " represents that the product of certain batch goes wrong, the product that " 0 " is certain batch is qualified, for example:
Decision rule [0010] shows if product batches P goes wrong, and all the other product batches are qualified, and milking station A has problem;
Decision rule [0011] shows if product batches P and Q go wrong, and product batches M and N are qualified, and milking station B has problem;
Decision rule [1000] shows if product batches M goes wrong, and all the other product batches are qualified, and milking station C has problem;
Decision rule [1100] shows if product batches M and N go wrong, and all the other product batches are qualified, and milking station D has problem.
Table 2
| M | N | P | Q | Defective food sources |
| 0 | 0 | 1 | 0 | The A milking station |
| 0 | 0 | 1 | 1 | The B milking station |
| 1 | 0 | 0 | 0 | The C milking station |
| 1 | 1 | 0 | 0 | The D milking station |
Therefore, if determine to only have a kind of raw material sources that problem is arranged, according to the method for above-described embodiment, can uniquely determine underproof raw material sources.
[the second embodiment]
to produce the family expenses liquid detergent as example, from chemical plant A, B, the industrial chemicals alkanolamide in C and D four chemical plant is that raw material sources are produced the family expenses liquid detergents, according to the production plan, produces M every day, N, P, the family expenses liquid detergent of Q and R5 batch, wherein the family expenses liquid detergent of each batch needs the alkanolamide of 2.4 volumes, A, B, the industrial chemicals alkanolamide that four chemical plant of C and D are transported to the chemical plant every day is respectively 2,2,4,4 volumes, and determine to occur the number in the chemical plant of quality problems≤2 according to historical record, according to the method for the embodiment of the present invention, at two-dimensional space, possible assay is encoded, determine that according to the number of the problematic raw material sources of possibility the coding spacing between any two capable vectors is 2, the row vector of wherein said two-dimensional space is corresponding to underproof chemical plant A, B, the combination of C and D, and the column vector of described two-dimensional space is corresponding to product batches M, N, P, Q and R, " 1 " represents that the product of certain batch goes wrong, the product that " 0 " is certain batch is qualified, the following encoder matrix B that meets the embodiment of the present invention that illustrates.
According to the products material combination of determining this product batches corresponding to the underproof bit of expression assay corresponding with single problematic raw material sources in the column vector of product batches, the combination of batch M is the alkanolamide from chemical plant C and D, the combination of batch N is the alkanolamide from chemical plant A and D, the combination of batch P is the alkanolamide from chemical plant A and B, the combination of batch Q is the alkanolamide from chemical plant B and C, and batch R is the alkanolamide from chemical plant C.again according to the quality of all batches and the principle of mass conservation of rule of origin, calculate the portfolio ratio of the products material of each batch, table 2 illustrates the portfolio ratio of the products material of each batch, the proportioning that calculates the family expenses liquid detergent of batch M is the alkanolamide in 0.4 volume C chemical plant and the alkanolamide in 2 volume D chemical plant, the proportioning of the family expenses liquid detergent of batch N is the alkanolamide in 0.4 volume A chemical plant and the alkanolamide in 2 volume D chemical plant, the proportioning of the family expenses liquid detergent of batch P is the alkanolamide in 1.6 volume A chemical plant and the alkanolamide in 0.8 volume B chemical plant, the proportioning of the family expenses liquid detergent of batch Q is the alkanolamide in 1.2 volume B chemical plant and the alkanolamide in 1.2 volume C chemical plant, the proportioning of the family expenses liquid detergent of batch R is the alkanolamide in 2.4 volume C chemical plant.
Table 3
| Product batches | The products material proportioning |
| M | C 0.4D 2 |
| N | A 0.4D 2 |
| P | A 1.6B 0.8 |
| Q | B 1.2C 1.2 |
| R | C 2.4 |
In the situation of the source of substandard product raw material≤2, determine the decision rule in substandard product source according to the row vector of originating corresponding to underproof products material in encoder matrix B, decision rule when table 4 illustrates product and quality problems occur, obtain the assay of the product batches relevant to decision rule, originate according to assay and the unique definite underproof products material of decision rule, wherein " 1 " represents that the product of certain batch goes wrong, and the product that " 0 " is certain batch is qualified, for example:
Decision rule [01100] shows if product batches N and P go wrong, and all the other product batches are qualified, and chemical plant A has problem;
Decision rule [00110] shows if product batches P and Q go wrong, and product batches M, Q and R are qualified, and chemical plant B has problem;
Decision rule [10011] shows if product batches M, Q and R go wrong, and product batches N and P are qualified, and chemical plant C has problem;
Decision rule [11000] shows if product batches M and N go wrong, and all the other product batches are qualified, and chemical plant D has problem;
Decision rule [01110] shows if product batches N, P and Q go wrong, and product batches M and R are qualified, and chemical plant A and B have problem;
Decision rule [11111] shows that chemical plant A and C have problem if product batches M, N, P, Q and R have problem;
Decision rule [11100] shows if product batches M, N and P go wrong, and product batches Q and R are qualified, and chemical plant A and D have problem;
Decision rule [10111] shows if product batches M, P, Q and R go wrong, and product batches N is qualified, and chemical plant B and C have problem;
Decision rule [11110] shows if product batches M, N, P and Q go wrong, and product batches R is qualified, and chemical plant B and D have problem;
Decision rule [11011] shows if product batches M, N, Q and R go wrong, and product batches P is qualified, and chemical plant C and D have problem.
Table 4
| M | N | P | Q | R | The substandard product source |
| 0 | 1 | 1 | 0 | 0 | Chemical plant A |
| 0 | 0 | 1 | 1 | 0 | Chemical plant B |
| 1 | 0 | 0 | 1 | 1 | Chemical plant C |
| 1 | 1 | 0 | 0 | 0 | Chemical plant D |
| 0 | 1 | 1 | 1 | 0 | Chemical plant A and B |
| 1 | 1 | 1 | 1 | 1 | Chemical plant A and C |
| 1 | 1 | 1 | 0 | 0 | Chemical plant A and D |
| 1 | 0 | 1 | 1 | 1 | Chemical plant B and C |
| 1 | 1 | 1 | 1 | 0 | Chemical plant B and D |
| 1 | 1 | 0 | 1 | 1 | Chemical plant C and D |
Below be listed in detail the concrete steps of judging according to the decision rule of table 4:
1) if batch N and P go wrong, because a batch M, Q and R are qualified, therefore can the deterministic B of factory, C and the raw material of D qualified, can determine that thus the raw material in A chemical plant is defective;
2) if batch P and Q go wrong, because a batch M, N and R are qualified, therefore can the deterministic A of factory, C and the raw material of D qualified, can determine that thus the raw material in B chemical plant is defective;
3) if batch M, Q and R go wrong, because batch N and P are qualified, therefore can the deterministic A of factory, B and the raw material of D qualified, can determine that thus the raw material in C chemical plant is defective;
4) if batch M and N go wrong, because a batch P, Q and R are qualified, therefore can the deterministic A of factory, B and the raw material of C qualified, can determine that thus the raw material in D chemical plant is defective.
5) if batch N, P and Q go wrong, because batch M and R are qualified, therefore can the deterministic C of factory and the raw material of D qualified, thus can the deterministic A of factory and the raw material of B defective;
6) if batch M, N, P, Q and R go wrong, therefore can the deterministic B of factory and the raw material of D qualified, thus can the deterministic A of factory and the raw material of C defective;
7) if batch M, P and N go wrong, because batch Q and R are qualified, therefore can the deterministic B of factory and the raw material of C qualified, thus can the deterministic A of factory and the raw material of D defective;
7) if batch M, P, Q and R go wrong, because a batch N is qualified, therefore can the deterministic A of factory and the raw material of D qualified, thus can the deterministic B of factory and the raw material of C defective;
8) if batch M, N, P and Q go wrong, because a batch R is qualified, therefore can the deterministic A of factory and the raw material of C qualified, thus can the deterministic B of factory and the raw material of D defective.
9) if batch M, N, Q and R go wrong, because a batch P is qualified, therefore can the deterministic A of factory and the raw material of B qualified, thus can the deterministic C of factory and the raw material of D defective.
[the 3rd embodiment]
Still take the production family expenses liquid detergent of the second embodiment as example, obtain the probability of the average security risk of the alkanolamide that raw material sources chemical plant A, B, C and D produce according to historical data, as shown in table 5.
Table 5
| Raw material sources | Chemical plant A | Chemical plant B | Chemical plant C | Chemical plant D |
| Average security risk | 5％ | 5％ | 30％ | 20％ |
The computing method of product risks probability:
The risk probability of certain batch products equals the risk of corresponding raw material: 4
Take table 3 as example, the risk probability of product batches M is:
r(M)＝r(C∪D)＝r(C)+r(D)-r(C)r(D)
Calculate r (M)=0.44
In like manner, the risk probability of product batches N is:
r(N)＝r(A∪D)＝r(A)+r(D)-r(A)r(D)
Calculate r (N)=0.24
The risk probability of product batches P is:
r(P)＝r(A∪B)＝r(A)+r(B)-r(A)r(B)
Calculate r (P)=0.075
r(Q)＝r(B∪C)＝r(B)+r(C)-r(B)r(C)
Calculate r (Q)=0.335
r(R)＝r(C)＝0.3
Table 6 illustrates the product risks probability corresponding to each batch of the second embodiment.
Table 6
| Product batches | The products material proportioning | Product risks |
| M | C 0.4D 2 | 0.44 |
| N | A 0.4D 2 | 0.24 |
| P | A 1.6B 0.8 | 0.075 |
| Q | B 1.2C 1.2 | 0.335 |
| R | C 2.4 | 0.30 |
Overall product risk=(r (M)+r (N)+r (P)+r (Q)+r (R))/5=0.278
Method according to the embodiment of the present invention, calculate qualified encoder matrix C, according to the products material combination of determining this product batches corresponding to the underproof bit of expression assay corresponding with single problematic raw material sources in the column vector of product batches, the combination of batch M is the alkanolamide from chemical plant B and C, the combination of batch N is the alkanolamide from chemical plant C, the combination of batch P is the alkanolamide from chemical plant D, the combination of batch Q is the alkanolamide from chemical plant A and B, and batch R is the alkanolamide from chemical plant A and D.again according to the quality of all batches and the principle of mass conservation of rule of origin, calculate the portfolio ratio of the products material of each batch, table 5 illustrates the portfolio ratio of the products material of each batch, the proportioning that calculates the family expenses liquid detergent of batch M is the alkanolamide in 0.8 volume B chemical plant and the alkanolamide in 1.6 volume C chemical plant, the proportioning of the family expenses liquid detergent of batch N is the alkanolamide in 2.4 volume C chemical plant, the proportioning of the family expenses liquid detergent of batch P is the alkanolamide in 2.4 volume D chemical plant, the proportioning of the family expenses liquid detergent of batch Q is the alkanolamide in 1.2 volume B chemical plant and the alkanolamide in 1.2 volume C chemical plant, the proportioning of the family expenses liquid detergent of batch R is the alkanolamide in 0.8 volume A chemical plant and the alkanolamide in 1.6 volume D chemical plant.
Table 7
| Product batches | The products material proportioning | Product risks |
| M | B 0.8C 1.6 | 0.335 |
| N | C 2.4 | 0.30 |
| P | D 2.4 | 0.20 |
| Q | A 1.2B 1.2 | 0.075 |
| R | A 0.8D 1.6 | 0.24 |
The risk probability of product batches M is:
r(M)＝r(B∪C)＝r(B)+r(C)-r(B)r(C)
Calculate r (M)=0.335
In like manner, the risk probability of product batches N is:
r(N)＝r(C)＝0.3
The risk probability of product batches P is:
r(P)＝r(D)＝0.2
r(Q)＝r(A∪B)＝r(A)+r(B)-r(A)r(B)
Calculate r (Q)=0.075
r(Q)＝r(A∪D)＝r(A)+r(D)-r(A)r(D)
Calculate r (Q)=0.24
Overall product risk=(r (M)+r (N)+r (P)+r (Q)+r (R))/5=0.23
Due to the overall product risk of the table 7 product overall risk less than the second embodiment, therefore choose the combinations produce product of table 7.
In the situation that the source of substandard product raw material≤2, determine the decision rule in substandard product source according to the row vector of originating corresponding to underproof products material in encoder matrix C, decision rule when table 8 illustrates product and quality problems occur, obtain the assay of the product batches relevant to decision rule, originate according to assay and the unique definite underproof products material of decision rule, wherein " 1 " represents that the product of certain batch goes wrong, and the product that " 0 " is certain batch is qualified, for example:
Decision rule [00011] shows if product batches Q and R are defective, and product batches M, N and P are qualified, and chemical plant A is defective;
Decision rule [10010] shows if product batches M and Q are defective, and product batches N, P and R are qualified, and chemical plant B is defective;
Decision rule [11000] shows if product batches M, N are defective, and product batches P, Q and R are qualified, and chemical plant C is defective;
Decision rule [00101] shows if product batches P and R are defective, and product batches M, N and Q are qualified, and chemical plant D is defective;
Decision rule [10011] shows if product batches M, Q and R are defective, and product batches N and P are qualified, and chemical plant A and B are defective;
Decision rule [11011] shows if product batches M, N, Q and R are defective, and product batches P is qualified, and chemical plant A and C are defective;
Decision rule [00110] shows if product batches P and Q are defective, and product batches M, N and R are qualified, and chemical plant A and D are defective;
Decision rule [11010] shows if product batches M, N, Q are defective, and product batches P and R are qualified, and chemical plant B and C are defective;
Decision rule [10111] shows if product batches M, P, Q and R are defective, and product batches N is qualified, and chemical plant B and D are defective;
Decision rule [11101] shows if product batches M, N, P and R are defective, and product batches Q is qualified, and chemical plant C and D are defective.
Table 8
| M | N | P | Q | R | The substandard product source |
| 0 | 0 | 0 | 1 | 1 | Chemical plant A |
| 1 | 0 | 0 | 1 | 0 | Chemical plant B |
| 1 | 1 | 0 | 0 | 0 | Chemical plant C |
| 0 | 0 | 1 | 0 | 1 | Chemical plant D |
| 1 | 0 | 0 | 1 | 0 | Chemical plant A and B |
| 1 | 1 | 0 | 1 | 1 | Chemical plant A and C |
| 0 | 0 | 1 | 1 | 0 | Chemical plant A and D |
| 1 | 1 | 0 | 1 | 0 | Chemical plant B and C |
| 1 | 0 | 1 | 1 | 1 | Chemical plant B and D |
| 1 | 1 | 1 | 0 | 1 | Chemical plant C and D |
Below be listed in detail the concrete detecting step of judging according to the decision rule of table 8:
1) batch M is defective, detects the quality of batch N,
1.1 if a batch N is qualified, detect the quality of batch P,
1.1.1 if a batch P is qualified, detect the quality of batch R,
If 1.1.1.1 R is qualified, the deterministic B of factory is defective
If 1.1.1.2 R is defective, the deterministic A of factory and B are defective
If 1.1.2 batch P is defective, the deterministic B of factory and D are defective
1.2 if batch N is defective, detect the quality of batch P
1.2.1 if a batch P is qualified, detect the quality of batch Q
If 1.2.1.1 Q is qualified, the deterministic C of factory is defective
1.2.1.2 if Q is defective, detect the quality of batch R
If 1.2.1.2.1 R is qualified, the deterministic B of factory and C are defective
If 1.2.1.2.2 R is defective, the deterministic A of factory and C are defective
If 1.2.2 batch P is defective, the deterministic C of factory and D are defective
2) if a batch N goes wrong, detect the quality of batch P,
2.1 if a batch P is qualified, detect the quality of batch Q,
If 2.1.1 a batch Q is qualified, the deterministic C of factory is defective
2.1.2 if batch Q is defective, detect the quality of batch R
If 2.1.2.1 R is qualified, the deterministic B of factory and C are defective
If 2.1.2.2 R is defective, the deterministic A of factory and C are defective
2.2 if batch P is defective, detect the quality of batch P,
If 2.2.1 a batch P is qualified, the deterministic C of factory and D are defective
3) if batch P is defective, detect the quality of batch N,
3.1 if a batch N is qualified, detect the quality of batch M,
3.1.1 if a batch P is qualified, detect the quality of batch Q,
If 3.1.1.1 Q is qualified, the deterministic D of factory is defective
If 3.1.1.2 Q is defective, the deterministic A of factory and D are defective
If 3.1.2 batch P is defective, the deterministic B of factory and D are defective
If 3.2 batch N is defective, the deterministic C of factory and D are defective
4) if batch Q is defective, detect the quality of batch M
4.1 if a batch M is qualified, detect the quality of batch P
4.1.1 if a batch P is qualified, detect the quality of batch N
4.1.1.1 if a batch N is qualified, detect the quality of batch R
If 4.1.1.1.1 a batch R is qualified, the deterministic B of factory is defective
If 4.1.1.1.2 batch R is defective, the deterministic A of factory and B are defective
4.1.1.2 if batch N is defective, detect the quality of batch R
If 4.1.1.2.1 a batch R is qualified, the deterministic B of factory and C are defective
If 4.1.1.2.2 batch R is defective, the deterministic A of factory and C are defective
If 4.1.2 batch P is defective, the deterministic B of factory and D are defective
4.2 if batch M is defective, detect the quality of batch P
If 4.2.1 a batch P is qualified, the deterministic A of factory is defective
If 4.2.2 batch P is defective, the deterministic A of factory and D are defective
5) if a batch R goes wrong, detect the quality of batch M
5.1 if a batch M is qualified, detect the quality of batch Q
If 5.1.1 a batch Q is qualified, the deterministic D of factory is defective
5.1.2 if batch Q is defective, detect the quality of batch P
If 5.1.2.1 a batch P is qualified, the deterministic A of factory is defective
If 5.1.2.2 batch P is defective, the deterministic A of factory and D are defective
5.2 if batch M is defective, detect the quality of batch Q
If 5.2.1 a batch Q is qualified, the deterministic C of factory and D are defective
5.2.2 if batch Q is defective, detect the quality of batch N
5.2.2.1 if a batch N is qualified, detect the quality of batch P
If 5.2.2.1.1 a batch P is qualified, the deterministic A of factory and B are defective
If 5.2.2.1.2 batch P is defective, the deterministic B of factory and D are defective
If 5.2.2.2 batch N is defective, the deterministic A of factory and C are defective
Based on same inventive concept, the present invention proposes a kind of product quality retrospective device, Fig. 4 illustrates product quality retrospective device according to an embodiment of the invention, this device comprises: optimize module 401, be configured to the product-based production schedule and produce the decision rule of originating corresponding to products material combination and the underproof products material of product batches; Production module 402 is configured to according to described products material combinations produce product; Determination module 403 is configured to quality problems occur in response to product, determines underproof products material source according to decision rule.
Wherein optimizing module 401 also comprises: acquisition module is configured to obtain raw material sources, product batches and number that may underproof raw material sources; And coding module, be configured to possible assay is encoded and produced encoder matrix at two-dimensional space based on the number of the raw material sources that obtain, product batches and the underproof raw material sources of possibility, wherein determine coding distance between any two capable vectors of encoder matrix according to number that may underproof raw material sources, the row vector of encoder matrix is corresponding to underproof products material source, the column vector of encoder matrix is corresponding to product batches, and wherein said coding meets following two conditions:
1) | s (f
-1(n
k))-s (f
-1(n
j)) | 〉=C, C 〉=0,1≤k, j≤N and k ≠ j, N ∈ positive integer;
2) q (m
i)=q (f (m
i)), 1≤i≤M, M ∈ positive integer;
M wherein
iRepresent i product batches; n
jAnd n
kRepresent respectively j and k raw material sources; .f () represents the component function of product batches; f
-1The inverse function of the component function of () expression product batches; Q () expression calculated mass function; The express possibility number in underproof products material source of s () expression binary coding function, C.
According to embodiments of the invention, wherein optimize module and further be configured to according to the products material combination of determining this product batches corresponding to the underproof bit of expression assay corresponding with single underproof raw material sources in the column vector of product batches.
According to embodiments of the invention, wherein optimize module and further be configured to according to the vectorial decision rule of determining the substandard product source of row corresponding to underproof products material source.
According to embodiments of the invention, wherein acquisition module further is configured to obtain the security risk coefficient of raw material sources.Wherein optimizing module further is configured to: the security risk of calculating described products material combination; Choose the products material combination of security risk minimum.
According to embodiments of the invention, wherein determination module further is configured to: obtain the assay of the product batches relevant to decision rule, originate according to assay and the unique definite underproof products material of decision rule.
Fig. 5 has schematically shown and can realize the block diagram of computing equipment according to an embodiment of the invention.Computer system shown in Fig. 8 comprises CPU (CPU (central processing unit)) 501, RAM (random access memory) 502, ROM (ROM (read-only memory)) 503, system bus 504, hard disk watch-dog 505, keyboard monitor 506, serial line interface watch-dog 507, parallel interface watch-dog 508, display monitoring device 509, hard disk 510, keyboard 511, serial external unit 512, parallel external unit 513 and display 514.In these parts, what be connected with system bus 504 has CPU 501, RAM502, ROM503, hard disk watch-dog 505, keyboard monitor 506, serial line interface watch-dog 507, parallel interface watch-dog 508 and a display monitoring device 509.Hard disk 510 is connected with hard disk watch-dog 505, keyboard 511 is connected with keyboard monitor 506, serial external unit 512 is connected with serial line interface watch-dog 507, and parallel external unit 513 is connected with parallel interface watch-dog 508, and display 514 is connected with display monitoring device 509.
In Fig. 5, the function of each parts is being well-known in the art, and structure shown in Figure 5 is also conventional.This structure not only is used for personal computer, and is used for handheld device, as Palm PC, PDA (personal digital assistant), mobile phone etc.In different application, for example be used for to realize including according to the user terminal of client modules of the present invention or when including server host according to network application server of the present invention, can add some parts to the structure shown in Fig. 5, perhaps some parts in Fig. 5 can be omitted.Whole system shown in Fig. 5 by usually be stored in hard disk 510 as software or be stored in EPROM or other nonvolatile memory in computer-readable instruction control.Software also can be downloaded from the network (not shown).Perhaps be stored in hard disk 510, the software of perhaps downloading from network can be loaded into RAM 502, and is carried out by CPU 501, in order to complete the function of being determined by software.
Although the computer system of describing in Fig. 5 can support according to technical scheme provided by the invention, this computer system is an example of computer system.It will be apparent to those skilled in the art that many other Computer System Design also can realize embodiments of the invention.
Although describe exemplary embodiment of the present invention here with reference to the accompanying drawings, but should be appreciated that and the invention is not restricted to these accurate embodiment, and in the situation that do not deviate from scope of the present invention and aim, those of ordinary skills can carry out to embodiment the modification of various variations.All such changes and modifications are intended to be included in scope of the present invention defined in the appended claims.
Should be appreciated that some aspect at least of the present invention can alternately realize with program product.The program of the relevant function of the present invention of definition can be sent to data-storage system or computer system by various signal bearing mediums, described signal bearing medium includes but not limited to, (for example can not write storage medium, CD-ROM), can write storage medium (for example, floppy disk, hard disk drive, read/write CD ROM, light medium) and the communication media such as the computing machine that comprises Ethernet and telephone network.Therefore it should be understood that in this type of signal bearing medium, when carrying or during the computer-readable instruction of the methodological function of management in the present invention of encoding, representing alternate embodiments of the present invention.The present invention can hardware, the mode of software, firmware or its combination realizes.The present invention can realize in a computer system in a concentrated manner, or with the distribution mode realization, in this distribution mode, different component distribution is in the computer system of some interconnection.Any computer system or other device that are suitable for carrying out the method for describing herein are all suitable.Preferably, the present invention realizes in the mode of the combination of computer software and multi-purpose computer hardware, in this implementation, when this computer program is loaded and carries out, control this computer system and make it carry out method of the present invention, or consist of system of the present invention.
The above has provided the explanation of the preferred embodiments of the present invention for illustrational purpose.The above-mentioned explanation of preferred embodiment is not limit, does not plan the present invention is confined to disclosed clear and definite form yet, and obviously in view of above-mentioned instruction, many modifications and variations are possible.Apparent this modifications and variations are included in the scope of the present invention that is limited by additional claim to one skilled in the art.
Claims (18)
1. product quality retroactive method comprises:
The product-based production schedule produces the decision rule of originating corresponding to products material combination and the underproof products material of product batches;
According to described products material combinations produce product;
Quality problems occur in response to product, determine underproof products material source according to decision rule.
2. method according to claim 1, wherein the product-based production schedule produces the decision rule of originating corresponding to products material combination and the underproof products material of product batches and comprises:
Obtain the number in the underproof products material of raw material sources, product batches and possibility source;
Possible assay is encoded and produced encoder matrix at two-dimensional space based on the number that the raw material sources that obtain, product batches and the underproof products material of possibility are originated.
3. method according to claim 2, the row vector of wherein said encoder matrix is corresponding to underproof products material source, the column vector of encoder matrix is corresponding to product batches, and the number that the coding distance products material underproof according to possibility between any two capable vectors of encoder matrix originated is determined.
4. method according to claim 3, wherein said coding meets following two conditions:
1) | s (f
-1(n
k))-s (f
-1(n
j)) | 〉=C, C 〉=0,1≤k, j≤N and k ≠ j, N ∈ positive integer;
2) q (m
i)=q (f (m
i)), 1≤i≤M, M ∈ positive integer;
M wherein
iRepresent i product batches; n
jAnd n
kRepresent respectively j and k raw material sources; The component function of f () expression product batches; f
-1The inverse function of the component function of () expression product batches; Q () expression calculated mass function; S () expression binary coding function; The express possibility number in underproof products material source of C.
5. method according to claim 3, wherein the product-based production schedule produces products material combination corresponding to product batches and comprises according to determining that corresponding to the underproof bit of expression assay corresponding with single underproof products material source in the column vector of product batches the products material of this product batches makes up.
6. method according to claim 3, wherein the product-based production schedule decision rule that produces underproof products material source comprises according to determine the decision rule in underproof products material source corresponding to the row vector in underproof products material source.
7. method according to claim 5, also comprise the security risk coefficient that obtains the products material source.
8. method according to claim 7, determine that wherein the products material combination of this product batches also comprises:
Calculate the security risk of described products material combination;
Choose the products material combination of security risk minimum.
9. method according to claim 6, wherein quality problems occur in response to product and determine that according to decision rule underproof products material source also comprises: obtain the assay of the product batches relevant to decision rule, according to assay with decision rule is unique determines that underproof products material originates.
10. product quality retrospective device comprises:
Optimize module, be configured to the product-based production schedule and produce the decision rule of originating corresponding to products material combination and the underproof products material of product batches;
The production module is configured to according to described products material combinations produce product;
Determination module is configured to quality problems occur in response to product, determines underproof products material source according to decision rule.
11. device according to claim 10 is wherein optimized module and is also comprised:
Acquisition module is configured to obtain the number in the underproof products material of raw material sources, product batches and possibility source;
Coding module is configured to possible assay is encoded and produced encoder matrix at two-dimensional space based on the number that the raw material sources that obtain, product batches and the underproof products material of possibility are originated.
12. device according to claim 11, the row vector of wherein said encoder matrix is corresponding to underproof products material source, the column vector of encoder matrix is corresponding to product batches, and the number that the coding distance products material underproof according to possibility between any two capable vectors of encoder matrix originated is determined.
13. device according to claim 12, wherein said coding meet following two conditions:
1) | s (f
-1(n
k))-s (f
-1(n
j)) | 〉=C, C 〉=0,1≤k, j≤N and k ≠ j, N ∈ positive integer;
2) q (m
i)=q (f (m
i)), 1≤i≤M, M ∈ positive integer;
M wherein
iRepresent i product batches; n
jAnd n
kRepresent respectively j and k raw material sources; The component function of f () expression product batches; f
-1The inverse function of the component function of () expression product batches; Q () expression calculated mass function; S () expression binary coding function; The express possibility number in underproof products material source of C.
14. device according to claim 12 is wherein optimized module and further is configured to according to determining that corresponding to the underproof bit of expression assay corresponding with single underproof products material source in the column vector of product batches the products material of this product batches makes up.
15. device according to claim 12 is wherein optimized module and further is configured to according to the vectorial decision rule of determining the substandard product source of row corresponding to underproof products material source.
16. device according to claim 14, wherein acquisition module further is configured to obtain the security risk coefficient in products material source.
17. device according to claim 16 is wherein optimized module and further is configured to:
Calculate the security risk of described products material combination;
Choose the products material combination of security risk minimum.
18. device according to claim 15, wherein determination module further is configured to: obtain the assay of the product batches relevant to decision rule, originate according to assay and the unique definite underproof products material of decision rule.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011103905793A CN103136671A (en) | 2011-11-30 | 2011-11-30 | Product quality tracing method and product quality tracing device |
| US13/687,266 US9230225B2 (en) | 2011-11-30 | 2012-11-28 | Product quality tracing to locate unsafe product material |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011103905793A CN103136671A (en) | 2011-11-30 | 2011-11-30 | Product quality tracing method and product quality tracing device |
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| Publication Number | Publication Date |
|---|---|
| CN103136671A true CN103136671A (en) | 2013-06-05 |
Family
ID=48467552
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2011103905793A Pending CN103136671A (en) | 2011-11-30 | 2011-11-30 | Product quality tracing method and product quality tracing device |
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| Country | Link |
|---|---|
| US (1) | US9230225B2 (en) |
| CN (1) | CN103136671A (en) |
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| CN111080323A (en) * | 2019-12-25 | 2020-04-28 | 中国联合网络通信集团有限公司 | Product quality tracing evaluation method and equipment |
| CN112446715A (en) * | 2021-02-01 | 2021-03-05 | 深圳华龙讯达信息技术股份有限公司 | Product tracing method based on industrial internet cloud platform |
| CN114595969A (en) * | 2022-03-08 | 2022-06-07 | 芯电智联(北京)科技有限公司 | NFC label production management system |
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| CN103455869A (en) * | 2013-06-28 | 2013-12-18 | 共青城赛龙通信技术有限责任公司 | Production management method and system |
| CN111695743B (en) * | 2020-06-23 | 2024-04-05 | 信阳农林学院 | Industrial food safety production monitoring method, device, equipment and storage medium |
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Also Published As
| Publication number | Publication date |
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| US9230225B2 (en) | 2016-01-05 |
| US20130138235A1 (en) | 2013-05-30 |
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